code: def test_model_detection_different_inputs(self):
      model = detr_resnet50(pretrained=False).eval()
      # support NestedTensor
      x = nested_tensor_from_tensor_list(
          [torch.rand(3, 200, 200), torch.rand(3, 200, 250)]
      )
      out = model(x)
      self.assertIn("pred_logits", out)
      # and 4d Tensor
      x = torch.rand(1, 3, 200, 200)
      out = model(x)
      self.assertIn("pred_logits", out)
      # and List[Tensor[C, H, W]]
      x = torch.rand(3, 200, 200)
      out = model([x])
      self.assertIn("pred_logits", out)
  
imports: import io
  import unittest
  import torch
  from torch import nn, Tensor
  from typing import List
  from models.matcher import HungarianMatcher
  from models.position_encoding import PositionEmbeddingSine, PositionEmbeddingLearned
  from models.backbone import Backbone, Joiner, BackboneBase
  from util import box_ops
  from util.misc import nested_tensor_from_tensor_list
  from hubconf import detr_resnet50, detr_resnet50_panoptic
label_desc: Use image node_id 8 for calling the Tester obj's underlying member method code with example usage: obj.test_model_detection_different_inputs() without return types